Recent publications
Article
Alzheimer’s Disease Neuroimaging Initiative 2022, 'A robust and interpretable machine learning approach using multimodal biological data to predict future pathological tau accumulation', Nature Communications, vol. 13, no. 1, 1887. https://doi.org/10.1038/s41467-022-28795-7
Taghribi, A, Canducci, M, Mastropietro, M, Rijcke, SD, Bunte, K & Tino, P 2022, 'ASAP – A sub-sampling approach for preserving topological structures modeled with geodesic topographic mapping', Neurocomputing, vol. 470, pp. 376-388. https://doi.org/10.1016/j.neucom.2021.05.108
Patel, K, Fernandez-villamarin, M, Ward, C, Lord, JM, Tino, P & Mendes, PM 2022, 'Establishing a quantitative fluorescence assay for the rapid detection of kynurenine in urine', The Analyst, vol. 147, no. 9, 1931, pp. 1931-1936. https://doi.org/10.1039/D2AN00107A
Mohammadi, M, Tino, P & Bunte, K 2022, 'Manifold alignment aware ants: a Markovian process for manifold extraction', Neural Computation, vol. 34, no. 3, pp. 595-641. https://doi.org/10.1162/neco_a_01478
Rodgers, N, Tino, P & Johnson, S 2022, 'Network hierarchy and pattern recovery in directed sparse Hopfield networks', Physical Review E, vol. 105, no. 6, 064304 . https://doi.org/10.1103/PhysRevE.105.064304
Canducci, M, Tino, P & Mastropietro, M 2022, 'Probabilistic modelling of general noisy multi-manifold data sets', Artificial Intelligence, vol. 302, 103579. https://doi.org/10.1016/j.artint.2021.103579
Goodman, T, Van Gemst, K & Tino, P 2021, 'A geometric framework for pitch estimation on acoustic musical signals', The Journal of Mathematics and Music. https://doi.org/10.1080/17459737.2021.1979116
Zhang, S, Tino, P & Yao, X 2021, 'Hierarchical reduced-space drift detection framework for multivariate supervised data streams', IEEE Transactions on Knowledge and Data Engineering. https://doi.org/10.1109/TKDE.2021.3111756
Verzelli, P, Alippi, C, Livi, L & Tino, P 2021, 'Input-to-state representation in linear reservoirs dynamics', IEEE Transactions on Neural Networks and Learning Systems. https://doi.org/10.1109/TNNLS.2021.3059389
Pauli, R, Kohls, G, Tino, P, Rogers, JC, Baumann, S, Ackermann, K, Bernhard, A, Martinelli, A, Jansen, L, Oldenhof, H, Gonzalez-Madruga, K, Smaragdi, A, Gonzalez-Torres, MA, Kerexeta-Lizeaga, I, Boonmann, C, Kersten, L, Bigorra, A, Hervas, A, Stadler, C, Fernandez-Rivas, A, Popma, A, Konrad, K, Herpertz-Dahlmann, B, Fairchild, G, Freitag, CM, Rotshtein, P & De Brito, SA 2021, 'Machine learning classification of conduct disorder with high versus low levels of callous-unemotional traits based on facial emotion recognition abilities', European Child and Adolescent Psychiatry. https://doi.org/10.1007/s00787-021-01893-5
Akerman, I, Kasaai, B, Bazarova, A, Sang, PB, Peiffer, I, Artufel, M, Derelle, R, Smith, G, Rodriguez-Martinez, M, Romano, M, Kinet, S, Tino, P, Theillet, C, Taylor, N, Ballester, B & Méchali, M 2020, 'A predictable conserved DNA base composition signature defines human core DNA replication origins', Nature Communications, vol. 11, no. 1, 4826 . https://doi.org/10.1038/s41467-020-18527-0
Conference contribution
Friess, S, Tiňo, P, Menzel, S, Sendhoff, B & Yao, X 2022, Predicting CMA-ES operators as inductive biases for shape optimization problems. in 2021 IEEE Symposium Series on Computational Intelligence (SSCI)., 9660001, IEEE Symposium Series on Computational Intelligence, Institute of Electrical and Electronics Engineers (IEEE), IEEE Symposium Series on Computational Intelligence (IEEE SSCI 2021), Orlando, Florida, United States, 5/12/21. https://doi.org/10.1109/SSCI50451.2021.9660001
Chen, X, Shen, Y, Zavala, E, Tsaneva-Atanasova, K, Upton, T, Russell, G & Tino, P 2022, SOMiMS - topographic mapping in the model space. in H Yin, D Camacho, P Tino, R Allmendinger, AJ Tallón-Ballesteros, K Tang, S-B Cho, P Novais & S Nascimento (eds), Intelligent Data Engineering and Automated Learning – IDEAL 2021 : 22nd International Conference, IDEAL 2021 Manchester, UK, November 25–27, 2021 Proceedings. Lecture Notes in Computer Science, vol. 13113, Springer Nature, pp. 502-510, The 22nd International Conference on Intelligent Data Engineering and Automated Learning (IDEAL), Manchester, United Kingdom, 25/11/21. https://doi.org/10.1007/978-3-030-91608-4_50
Friess, S, Tiňo, P, Xu, Z, Menzel, S, Sendhoff, B & Yao, X 2021, Artificial neural networks as feature extractors in continuous evolutionary optimization. in 2021 International Joint Conference on Neural Networks (IJCNN)., 9533915, International Joint Conference on Neural Networks (IJCNN), IEEE, pp. 1-9, 2021 International Joint Conference on Neural Networks (IJCNN), 18/07/21. https://doi.org/10.1109/IJCNN52387.2021.9533915
Canducci, M, Taghribi, A, Mastropietro, M, Rijcke, SD, Peletier, R, Bunte, K & Tino, P 2021, Tracking the temporal-evolution of supernova bubbles in numerical simulations. in H Yin, D Camacho, P Tino, R Allmendinger, AJ Tallón-Ballesteros, K Tang, S-B Cho, P Novais & S Nascimento (eds), Intelligent Data Engineering and Automated Learning – IDEAL 2021: 22nd International Conference, IDEAL 2021, Manchester, UK, November 25–27, 2021, Proceedings. 1 edn, Lecture Notes in Computer Science , vol. 13113, Springer, Cham, pp. 493–501, The 22nd International Conference on Intelligent Data Engineering and Automated Learning (IDEAL), Manchester, United Kingdom, 25/11/21. https://doi.org/10.1007/978-3-030-91608-4_49
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